tmu_gfm_dataset

Referências:

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:tmu_gfm_dataset')
  • Descrição :
A dataset for GEC metrics with manual evaluations of grammaticality, fluency, and meaning preservation for system outputs. More detail about the creation of the dataset can be found in Yoshimura et al. (2020).
  • Licença : Nenhuma licença conhecida
  • Versão : 1.1.0
  • Divisões :
Dividir Exemplos
'train' 4221
  • Características :
{
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "output": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "grammer": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "fluency": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "meaning": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "system": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ave_g": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    },
    "ave_f": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    },
    "ave_m": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    }
}